Checkr Staff Data Engineer at Checkr responsible for designing and building core services and data pipelines for the centralized data platform. Leads execution of scalable, reliable data solutions supporting fair and safe hiring decisions.
Responsibilities
Design, build, and ship core services and data pipelines for Checkr's centralized data platform
Bring a customer-centric, product-oriented mindset to the table by collaborating with customers and internal stakeholders to resolve product ambiguities and ship impactful features
Partner with engineering, product, and data teams across Workforce, Tenant, Trust, and Personal to turn ambiguous problems into shipped features
Experimentation mindset: autonomy and empowerment to validate a customer need, get team buy-in, and ship a rapid MVP
Deliver performant, reliable, and secure code, with quality and testing as a default rather than a phase
Participate in on-call; monitor, triage, and resolve production issues for services the team owns
Mentor engineers and raise the bar through design and code review
5+ years of development experience in the field of software engineering, preferably working with data
Strong proficiency in Python or similar languages, and strong SQL skills
Experience with ETL/ELT, and stream and batch processing of data at scale
Experience running data processing workloads in the cloud at scale; AWS expertise (S3, EMR, Glue, Athena, EKS, Lambda) preferred
Comfort working with AI tools day-to-day, and the ability to build simple AI-powered tools or workflows that boost team or org productivity
Qualification
Expert-level proficiency in PySparkExpertise in data modelingExperience with real-timePay Transparency Disclosure$224
Required
10+ years designing and delivering scalable data platforms
Experience with large-scale data processing pipelines using ETL/ELT, batch, and stream processing
Expert-level proficiency in PySpark, Python, and SQL
Expertise in data modeling, relational databases, and NoSQL data stores
Experience with big data technologies such as Kafka, Spark, Iceberg, data lakes, and AWS stack
Preferred
Experience with big data technologies such as PySpark, Kafka, Spark, Iceberg, and Datalake architectures
Experience with real-time, low-latency data processing
Experience/knowledge of data processing platforms such as Databricks or Snowflake.
An understanding of Graph and Vector data stores
Pay Transparency Disclosure
We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see our website.
On-target Earnings OR Base Salary range (San Francisco, CA)
